Intro to Data Science in San Francisco

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Intro to Data Science

Data Science is a burgeoning new field in high demand, but for aspiring data scientists the path to becoming one is long and winding. No one can quite put their finger on what makes a great data scientist, or how we can train people in the techniques necessary to become one. Aimed at beginners looking to break into the field, we will explore the practice of data analysis through hands-on examples.

Interested in attending but live elsewhere? Have a scheduling conflict? Due to popular demand we are now offering this class remotely! Buy a "Virtual" ticket and gain access to an online discussion board where the instructors answer all your questions, receive a video of the lecture, and get all the class materials.

Prerequisites

A childlike curiosity.

About Your Teachers

Jonathan and Ryan are the founders of Zipfian Academy, a school which trains the next generation of Data Scientists.

Jonathan first discovered his love of all things data while studying Computer Science and Physics at UC Berkeley. In a former life, he worked for Alpine Data Labs developing distributed machine learning algorithms for predictive analytics on Hadoop.

Jonathan has always had a passion for sharing the things he has learned in the most creative ways he can. He has been a mentor at Dev Bootcamp, taught classes at General Assembly, and is an instructor at Hack Reactor where he gets to combine his two favorite things: humans and code.

Ryan is fascinated by data in all its forms, binary and biological. Trained in Genetics and Genomics at UC Berkeley, he plumbed the depths of plant immunity at the Plant Gene Expression Center, building big data applications targeting next-generation sequencing technologies.

As a Sr. Systems Engineer at Nutanix, he worked on scale-out distributed computing solutions for virtualized environments. When not trying to pull beauty out of data, you can find Ryan hacking on 3D printers, DIY Bio, and open-source hardware.